ARC-I. The ARC-I [1]} network employs a convolutional approach for semantic similarity measurements. It leverages pre-trained word embeddings, and several layers of convolutions and max-pooling to generate separate dense representations for queries and documents. Finally, it applies an MLP to compare the resulting vectors via a non-linear similarity function.
